Overview

Dataset statistics

Number of variables18
Number of observations4969
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory866.6 KiB
Average record size in memory178.6 B

Variable types

Numeric15
Boolean3

Alerts

voice_messages is highly overall correlated with voice_planHigh correlation
intl_mins is highly overall correlated with intl_chargeHigh correlation
intl_charge is highly overall correlated with intl_minsHigh correlation
day_mins is highly overall correlated with day_chargeHigh correlation
day_charge is highly overall correlated with day_minsHigh correlation
eve_mins is highly overall correlated with eve_chargeHigh correlation
eve_charge is highly overall correlated with eve_minsHigh correlation
night_mins is highly overall correlated with night_chargeHigh correlation
night_charge is highly overall correlated with night_minsHigh correlation
voice_plan is highly overall correlated with voice_messagesHigh correlation
intl_plan is highly imbalanced (54.8%)Imbalance
voice_messages has 3655 (73.6%) zerosZeros
customer_calls has 1016 (20.4%) zerosZeros

Reproduction

Analysis started2023-03-08 07:15:14.664450
Analysis finished2023-03-08 07:16:45.526148
Duration1 minute and 30.86 seconds
Software versionpandas-profiling v3.6.6
Download configurationconfig.json

Variables

account_length
Real number (ℝ)

Distinct218
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean100.20668
Minimum1
Maximum243
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size77.6 KiB
2023-03-08T12:46:46.041668image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile35
Q173
median100
Q3127
95-th percentile166.6
Maximum243
Range242
Interquartile range (IQR)54

Descriptive statistics

Standard deviation39.695476
Coefficient of variation (CV)0.39613602
Kurtosis-0.097760643
Mean100.20668
Median Absolute Deviation (MAD)27
Skewness0.11246768
Sum497927
Variance1575.7308
MonotonicityNot monotonic
2023-03-08T12:46:46.471969image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
90 64
 
1.3%
87 59
 
1.2%
105 57
 
1.1%
93 57
 
1.1%
112 56
 
1.1%
101 55
 
1.1%
86 55
 
1.1%
100 54
 
1.1%
103 54
 
1.1%
116 54
 
1.1%
Other values (208) 4404
88.6%
ValueCountFrequency (%)
1 11
0.2%
2 2
 
< 0.1%
3 8
0.2%
4 3
 
0.1%
5 2
 
< 0.1%
6 2
 
< 0.1%
7 5
0.1%
8 2
 
< 0.1%
9 3
 
0.1%
10 3
 
0.1%
ValueCountFrequency (%)
243 1
 
< 0.1%
238 1
 
< 0.1%
233 1
 
< 0.1%
232 2
< 0.1%
225 2
< 0.1%
224 2
< 0.1%
222 2
< 0.1%
221 1
 
< 0.1%
217 3
0.1%
216 1
 
< 0.1%

voice_plan
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size43.7 KiB
False
3654 
True
1315 
ValueCountFrequency (%)
False 3654
73.5%
True 1315
 
26.5%
2023-03-08T12:46:46.743582image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

voice_messages
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct48
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.7548803
Minimum0
Maximum52
Zeros3655
Zeros (%)73.6%
Negative0
Negative (%)0.0%
Memory size77.6 KiB
2023-03-08T12:46:46.962319image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q317
95-th percentile37
Maximum52
Range52
Interquartile range (IQR)17

Descriptive statistics

Standard deviation13.545738
Coefficient of variation (CV)1.7467372
Kurtosis0.20073976
Mean7.7548803
Median Absolute Deviation (MAD)0
Skewness1.3508024
Sum38534
Variance183.48701
MonotonicityNot monotonic
2023-03-08T12:46:47.231350image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
0 3655
73.6%
31 83
 
1.7%
28 67
 
1.3%
29 67
 
1.3%
33 66
 
1.3%
24 63
 
1.3%
27 63
 
1.3%
30 58
 
1.2%
26 57
 
1.1%
32 56
 
1.1%
Other values (38) 734
 
14.8%
ValueCountFrequency (%)
0 3655
73.6%
4 1
 
< 0.1%
6 2
 
< 0.1%
8 2
 
< 0.1%
9 2
 
< 0.1%
10 4
 
0.1%
11 2
 
< 0.1%
12 11
 
0.2%
13 4
 
0.1%
14 9
 
0.2%
ValueCountFrequency (%)
52 1
 
< 0.1%
51 1
 
< 0.1%
50 2
 
< 0.1%
49 3
 
0.1%
48 5
 
0.1%
47 4
 
0.1%
46 8
0.2%
45 11
0.2%
44 9
0.2%
43 16
0.3%

intl_plan
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size43.7 KiB
False
4499 
True
470 
ValueCountFrequency (%)
False 4499
90.5%
True 470
 
9.5%
2023-03-08T12:46:47.481351image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

intl_mins
Real number (ℝ)

Distinct170
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.264198
Minimum0
Maximum20
Zeros24
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size77.6 KiB
2023-03-08T12:46:47.701147image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5.7
Q18.5
median10.3
Q312
95-th percentile14.7
Maximum20
Range20
Interquartile range (IQR)3.5

Descriptive statistics

Standard deviation2.7619963
Coefficient of variation (CV)0.26909031
Kurtosis0.65321072
Mean10.264198
Median Absolute Deviation (MAD)1.8
Skewness-0.20857912
Sum51002.8
Variance7.6286234
MonotonicityNot monotonic
2023-03-08T12:46:48.013602image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11.1 89
 
1.8%
9.8 87
 
1.8%
11.3 82
 
1.7%
10.1 81
 
1.6%
11.4 81
 
1.6%
9.7 79
 
1.6%
10.6 78
 
1.6%
10.9 78
 
1.6%
10 77
 
1.5%
10.2 77
 
1.5%
Other values (160) 4160
83.7%
ValueCountFrequency (%)
0 24
0.5%
0.4 1
 
< 0.1%
1.1 2
 
< 0.1%
1.3 1
 
< 0.1%
2 3
 
0.1%
2.1 2
 
< 0.1%
2.2 1
 
< 0.1%
2.4 1
 
< 0.1%
2.5 1
 
< 0.1%
2.6 1
 
< 0.1%
ValueCountFrequency (%)
20 1
< 0.1%
19.7 2
< 0.1%
19.3 1
< 0.1%
19.2 1
< 0.1%
18.9 2
< 0.1%
18.7 1
< 0.1%
18.5 1
< 0.1%
18.4 1
< 0.1%
18.3 1
< 0.1%
18.2 2
< 0.1%

intl_calls
Real number (ℝ)

Distinct21
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.4330851
Minimum0
Maximum20
Zeros24
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size77.6 KiB
2023-03-08T12:46:48.279834image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median4
Q36
95-th percentile9
Maximum20
Range20
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.4594948
Coefficient of variation (CV)0.55480432
Kurtosis3.2751134
Mean4.4330851
Median Absolute Deviation (MAD)1
Skewness1.363577
Sum22028
Variance6.0491145
MonotonicityNot monotonic
2023-03-08T12:46:48.482952image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
3 988
19.9%
4 946
19.0%
2 739
14.9%
5 699
14.1%
6 491
9.9%
7 307
 
6.2%
1 265
 
5.3%
8 169
 
3.4%
9 148
 
3.0%
10 75
 
1.5%
Other values (11) 142
 
2.9%
ValueCountFrequency (%)
0 24
 
0.5%
1 265
 
5.3%
2 739
14.9%
3 988
19.9%
4 946
19.0%
5 699
14.1%
6 491
9.9%
7 307
 
6.2%
8 169
 
3.4%
9 148
 
3.0%
ValueCountFrequency (%)
20 1
 
< 0.1%
19 2
 
< 0.1%
18 4
 
0.1%
17 2
 
< 0.1%
16 7
 
0.1%
15 9
 
0.2%
14 6
 
0.1%
13 19
0.4%
12 23
0.5%
11 45
0.9%

intl_charge
Real number (ℝ)

Distinct170
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.7718515
Minimum0
Maximum5.4
Zeros24
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size77.6 KiB
2023-03-08T12:46:48.766248image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.54
Q12.3
median2.78
Q33.24
95-th percentile3.97
Maximum5.4
Range5.4
Interquartile range (IQR)0.94

Descriptive statistics

Standard deviation0.74567167
Coefficient of variation (CV)0.26901574
Kurtosis0.65383508
Mean2.7718515
Median Absolute Deviation (MAD)0.48
Skewness-0.20888467
Sum13773.33
Variance0.55602624
MonotonicityNot monotonic
2023-03-08T12:46:49.047480image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 89
 
1.8%
2.65 87
 
1.8%
3.05 82
 
1.7%
2.73 81
 
1.6%
3.08 81
 
1.6%
2.62 79
 
1.6%
2.86 78
 
1.6%
2.94 78
 
1.6%
2.7 77
 
1.5%
2.75 77
 
1.5%
Other values (160) 4160
83.7%
ValueCountFrequency (%)
0 24
0.5%
0.11 1
 
< 0.1%
0.3 2
 
< 0.1%
0.35 1
 
< 0.1%
0.54 3
 
0.1%
0.57 2
 
< 0.1%
0.59 1
 
< 0.1%
0.65 1
 
< 0.1%
0.68 1
 
< 0.1%
0.7 1
 
< 0.1%
ValueCountFrequency (%)
5.4 1
< 0.1%
5.32 2
< 0.1%
5.21 1
< 0.1%
5.18 1
< 0.1%
5.1 2
< 0.1%
5.05 1
< 0.1%
5 1
< 0.1%
4.97 1
< 0.1%
4.94 1
< 0.1%
4.91 2
< 0.1%

day_mins
Real number (ℝ)

Distinct1957
Distinct (%)39.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean180.30618
Minimum0
Maximum351.5
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size77.6 KiB
2023-03-08T12:46:49.377533image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile91.7
Q1143.7
median180.1
Q3216.2
95-th percentile271.16
Maximum351.5
Range351.5
Interquartile range (IQR)72.5

Descriptive statistics

Standard deviation53.931206
Coefficient of variation (CV)0.29910903
Kurtosis-0.020161323
Mean180.30618
Median Absolute Deviation (MAD)36.3
Skewness-0.01259556
Sum895941.4
Variance2908.575
MonotonicityNot monotonic
2023-03-08T12:46:49.657460image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
189.3 10
 
0.2%
174.5 9
 
0.2%
184.5 9
 
0.2%
159.5 9
 
0.2%
177.1 9
 
0.2%
154 9
 
0.2%
180 9
 
0.2%
168.6 8
 
0.2%
189.8 8
 
0.2%
168.4 8
 
0.2%
Other values (1947) 4881
98.2%
ValueCountFrequency (%)
0 2
< 0.1%
2.6 1
< 0.1%
6.6 1
< 0.1%
7.2 1
< 0.1%
7.8 1
< 0.1%
7.9 1
< 0.1%
12.5 1
< 0.1%
17.6 1
< 0.1%
18.9 1
< 0.1%
19.5 1
< 0.1%
ValueCountFrequency (%)
351.5 1
< 0.1%
350.8 1
< 0.1%
346.8 1
< 0.1%
345.3 1
< 0.1%
338.4 1
< 0.1%
337.4 1
< 0.1%
335.5 1
< 0.1%
334.3 1
< 0.1%
332.9 1
< 0.1%
332.1 1
< 0.1%

day_calls
Real number (ℝ)

Distinct123
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean100.02194
Minimum0
Maximum165
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size77.6 KiB
2023-03-08T12:46:49.925605image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile67
Q187
median100
Q3113
95-th percentile133
Maximum165
Range165
Interquartile range (IQR)26

Descriptive statistics

Standard deviation19.835965
Coefficient of variation (CV)0.19831615
Kurtosis0.18538539
Mean100.02194
Median Absolute Deviation (MAD)13
Skewness-0.086276974
Sum497009
Variance393.4655
MonotonicityNot monotonic
2023-03-08T12:46:50.200409image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
105 117
 
2.4%
102 113
 
2.3%
95 107
 
2.2%
94 104
 
2.1%
97 104
 
2.1%
112 101
 
2.0%
100 101
 
2.0%
108 100
 
2.0%
92 100
 
2.0%
106 99
 
2.0%
Other values (113) 3923
78.9%
ValueCountFrequency (%)
0 2
< 0.1%
30 1
 
< 0.1%
34 1
 
< 0.1%
35 1
 
< 0.1%
36 1
 
< 0.1%
39 2
< 0.1%
40 2
< 0.1%
42 2
< 0.1%
44 4
0.1%
45 3
0.1%
ValueCountFrequency (%)
165 1
 
< 0.1%
163 1
 
< 0.1%
160 2
 
< 0.1%
158 3
0.1%
157 2
 
< 0.1%
156 3
0.1%
152 2
 
< 0.1%
151 7
0.1%
150 6
0.1%
149 2
 
< 0.1%

day_charge
Real number (ℝ)

Distinct1957
Distinct (%)39.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.652604
Minimum0
Maximum59.76
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size77.6 KiB
2023-03-08T12:46:50.506782image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile15.59
Q124.43
median30.62
Q336.75
95-th percentile46.096
Maximum59.76
Range59.76
Interquartile range (IQR)12.32

Descriptive statistics

Standard deviation9.1682749
Coefficient of variation (CV)0.29910264
Kurtosis-0.020032265
Mean30.652604
Median Absolute Deviation (MAD)6.17
Skewness-0.012591406
Sum152312.79
Variance84.057264
MonotonicityNot monotonic
2023-03-08T12:46:50.898593image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
32.18 10
 
0.2%
29.67 9
 
0.2%
31.37 9
 
0.2%
27.12 9
 
0.2%
30.11 9
 
0.2%
26.18 9
 
0.2%
30.6 9
 
0.2%
28.66 8
 
0.2%
32.27 8
 
0.2%
28.63 8
 
0.2%
Other values (1947) 4881
98.2%
ValueCountFrequency (%)
0 2
< 0.1%
0.44 1
< 0.1%
1.12 1
< 0.1%
1.22 1
< 0.1%
1.33 1
< 0.1%
1.34 1
< 0.1%
2.13 1
< 0.1%
2.99 1
< 0.1%
3.21 1
< 0.1%
3.32 1
< 0.1%
ValueCountFrequency (%)
59.76 1
< 0.1%
59.64 1
< 0.1%
58.96 1
< 0.1%
58.7 1
< 0.1%
57.53 1
< 0.1%
57.36 1
< 0.1%
57.04 1
< 0.1%
56.83 1
< 0.1%
56.59 1
< 0.1%
56.46 1
< 0.1%

eve_mins
Real number (ℝ)

Distinct1875
Distinct (%)37.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean200.61737
Minimum0
Maximum363.7
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size77.6 KiB
2023-03-08T12:46:51.215506image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile118.44
Q1166.4
median201
Q3234.1
95-th percentile283.46
Maximum363.7
Range363.7
Interquartile range (IQR)67.7

Descriptive statistics

Standard deviation50.55059
Coefficient of variation (CV)0.25197514
Kurtosis0.053536201
Mean200.61737
Median Absolute Deviation (MAD)34
Skewness-0.013029395
Sum996867.7
Variance2555.3621
MonotonicityNot monotonic
2023-03-08T12:46:51.492671image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
230.9 10
 
0.2%
169.9 10
 
0.2%
199.7 10
 
0.2%
187.5 9
 
0.2%
223.5 9
 
0.2%
216.5 9
 
0.2%
210.6 9
 
0.2%
194 9
 
0.2%
188.8 9
 
0.2%
187 9
 
0.2%
Other values (1865) 4876
98.1%
ValueCountFrequency (%)
0 1
< 0.1%
22.3 1
< 0.1%
31.2 1
< 0.1%
37.8 1
< 0.1%
41.7 1
< 0.1%
42.2 1
< 0.1%
42.5 1
< 0.1%
43.9 1
< 0.1%
47.3 2
< 0.1%
48.1 1
< 0.1%
ValueCountFrequency (%)
363.7 1
< 0.1%
361.8 1
< 0.1%
359.3 1
< 0.1%
354.2 1
< 0.1%
352.1 1
< 0.1%
351.6 1
< 0.1%
350.9 1
< 0.1%
350.5 1
< 0.1%
349.4 1
< 0.1%
348.9 1
< 0.1%

eve_calls
Real number (ℝ)

Distinct126
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean100.17488
Minimum0
Maximum170
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size77.6 KiB
2023-03-08T12:46:51.808718image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile67
Q187
median100
Q3113
95-th percentile133
Maximum170
Range170
Interquartile range (IQR)26

Descriptive statistics

Standard deviation19.833572
Coefficient of variation (CV)0.19798947
Kurtosis0.12012961
Mean100.17488
Median Absolute Deviation (MAD)13
Skewness-0.019057289
Sum497769
Variance393.37058
MonotonicityNot monotonic
2023-03-08T12:46:52.089947image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
105 112
 
2.3%
97 110
 
2.2%
91 109
 
2.2%
94 106
 
2.1%
103 105
 
2.1%
101 104
 
2.1%
96 100
 
2.0%
109 99
 
2.0%
98 99
 
2.0%
102 99
 
2.0%
Other values (116) 3926
79.0%
ValueCountFrequency (%)
0 1
 
< 0.1%
12 1
 
< 0.1%
36 1
 
< 0.1%
37 1
 
< 0.1%
38 1
 
< 0.1%
42 1
 
< 0.1%
43 1
 
< 0.1%
44 2
 
< 0.1%
45 1
 
< 0.1%
46 5
0.1%
ValueCountFrequency (%)
170 1
 
< 0.1%
169 1
 
< 0.1%
168 1
 
< 0.1%
164 1
 
< 0.1%
159 1
 
< 0.1%
157 1
 
< 0.1%
156 1
 
< 0.1%
155 5
0.1%
154 4
0.1%
153 1
 
< 0.1%

eve_charge
Real number (ℝ)

Distinct1655
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.052695
Minimum0
Maximum30.91
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size77.6 KiB
2023-03-08T12:46:52.435775image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10.064
Q114.14
median17.09
Q319.9
95-th percentile24.096
Maximum30.91
Range30.91
Interquartile range (IQR)5.76

Descriptive statistics

Standard deviation4.2967842
Coefficient of variation (CV)0.25197098
Kurtosis0.053453799
Mean17.052695
Median Absolute Deviation (MAD)2.89
Skewness-0.01300597
Sum84734.84
Variance18.462355
MonotonicityNot monotonic
2023-03-08T12:46:52.779497image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14.25 15
 
0.3%
15.9 15
 
0.3%
16.12 14
 
0.3%
18.96 13
 
0.3%
18.79 13
 
0.3%
16.97 13
 
0.3%
19.41 12
 
0.2%
16.18 11
 
0.2%
17.82 11
 
0.2%
17.99 11
 
0.2%
Other values (1645) 4841
97.4%
ValueCountFrequency (%)
0 1
< 0.1%
1.9 1
< 0.1%
2.65 1
< 0.1%
3.21 1
< 0.1%
3.54 1
< 0.1%
3.59 1
< 0.1%
3.61 1
< 0.1%
3.73 1
< 0.1%
4.02 2
< 0.1%
4.09 1
< 0.1%
ValueCountFrequency (%)
30.91 1
< 0.1%
30.75 1
< 0.1%
30.54 1
< 0.1%
30.11 1
< 0.1%
29.93 1
< 0.1%
29.89 1
< 0.1%
29.83 1
< 0.1%
29.79 1
< 0.1%
29.7 1
< 0.1%
29.66 1
< 0.1%

night_mins
Real number (ℝ)

Distinct1849
Distinct (%)37.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean200.43467
Minimum0
Maximum395
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size77.6 KiB
2023-03-08T12:46:53.203431image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile117.34
Q1167.1
median200.4
Q3234.7
95-th percentile283.32
Maximum395
Range395
Interquartile range (IQR)67.6

Descriptive statistics

Standard deviation50.528158
Coefficient of variation (CV)0.2520929
Kurtosis0.088405815
Mean200.43467
Median Absolute Deviation (MAD)33.7
Skewness0.017947611
Sum995959.9
Variance2553.0947
MonotonicityNot monotonic
2023-03-08T12:46:53.503373image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
194.3 11
 
0.2%
188.2 11
 
0.2%
186.2 11
 
0.2%
228.1 10
 
0.2%
214.6 10
 
0.2%
214.7 9
 
0.2%
191.4 9
 
0.2%
197.4 9
 
0.2%
210 9
 
0.2%
169.4 9
 
0.2%
Other values (1839) 4871
98.0%
ValueCountFrequency (%)
0 1
< 0.1%
23.2 1
< 0.1%
43.7 1
< 0.1%
45 1
< 0.1%
46.7 1
< 0.1%
47.4 1
< 0.1%
50.1 2
< 0.1%
50.9 1
< 0.1%
53.3 1
< 0.1%
54 1
< 0.1%
ValueCountFrequency (%)
395 1
< 0.1%
381.9 1
< 0.1%
381.6 1
< 0.1%
377.5 1
< 0.1%
367.7 1
< 0.1%
364.9 1
< 0.1%
364.3 1
< 0.1%
359.9 1
< 0.1%
355.1 1
< 0.1%
354.9 1
< 0.1%

night_calls
Real number (ℝ)

Distinct131
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean99.954518
Minimum0
Maximum175
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size77.6 KiB
2023-03-08T12:46:53.837486image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile67
Q187
median100
Q3113
95-th percentile132
Maximum175
Range175
Interquartile range (IQR)26

Descriptive statistics

Standard deviation19.959015
Coefficient of variation (CV)0.19968096
Kurtosis0.15001524
Mean99.954518
Median Absolute Deviation (MAD)13
Skewness0.0016140032
Sum496674
Variance398.36226
MonotonicityNot monotonic
2023-03-08T12:46:54.112704image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
105 120
 
2.4%
102 109
 
2.2%
104 106
 
2.1%
100 106
 
2.1%
103 104
 
2.1%
99 104
 
2.1%
94 103
 
2.1%
95 102
 
2.1%
98 102
 
2.1%
91 100
 
2.0%
Other values (121) 3913
78.7%
ValueCountFrequency (%)
0 1
 
< 0.1%
12 1
 
< 0.1%
33 1
 
< 0.1%
36 1
 
< 0.1%
38 2
< 0.1%
40 1
 
< 0.1%
41 1
 
< 0.1%
42 4
0.1%
43 1
 
< 0.1%
44 1
 
< 0.1%
ValueCountFrequency (%)
175 1
< 0.1%
170 1
< 0.1%
168 1
< 0.1%
166 1
< 0.1%
165 1
< 0.1%
164 1
< 0.1%
161 1
< 0.1%
160 1
< 0.1%
159 2
< 0.1%
158 2
< 0.1%

night_charge
Real number (ℝ)

Distinct1028
Distinct (%)20.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.01967
Minimum0
Maximum17.77
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size77.6 KiB
2023-03-08T12:46:54.430440image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5.28
Q17.52
median9.02
Q310.56
95-th percentile12.746
Maximum17.77
Range17.77
Interquartile range (IQR)3.04

Descriptive statistics

Standard deviation2.2737761
Coefficient of variation (CV)0.25209083
Kurtosis0.088423978
Mean9.01967
Median Absolute Deviation (MAD)1.52
Skewness0.017914066
Sum44818.74
Variance5.1700578
MonotonicityNot monotonic
2023-03-08T12:46:54.771025image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.47 19
 
0.4%
9.66 19
 
0.4%
10.8 18
 
0.4%
10.26 18
 
0.4%
8.15 18
 
0.4%
9.63 18
 
0.4%
10.49 17
 
0.3%
9.4 17
 
0.3%
9.45 17
 
0.3%
9.76 16
 
0.3%
Other values (1018) 4792
96.4%
ValueCountFrequency (%)
0 1
< 0.1%
1.04 1
< 0.1%
1.97 1
< 0.1%
2.03 1
< 0.1%
2.1 1
< 0.1%
2.13 1
< 0.1%
2.25 2
< 0.1%
2.29 1
< 0.1%
2.4 1
< 0.1%
2.43 1
< 0.1%
ValueCountFrequency (%)
17.77 1
< 0.1%
17.19 1
< 0.1%
17.17 1
< 0.1%
16.99 1
< 0.1%
16.55 1
< 0.1%
16.42 1
< 0.1%
16.39 1
< 0.1%
16.2 1
< 0.1%
15.98 1
< 0.1%
15.97 1
< 0.1%

customer_calls
Real number (ℝ)

Distinct10
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5719461
Minimum0
Maximum9
Zeros1016
Zeros (%)20.4%
Negative0
Negative (%)0.0%
Memory size77.6 KiB
2023-03-08T12:46:55.038759image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.307458
Coefficient of variation (CV)0.8317448
Kurtosis1.4821675
Mean1.5719461
Median Absolute Deviation (MAD)1
Skewness1.0428282
Sum7811
Variance1.7094463
MonotonicityNot monotonic
2023-03-08T12:46:55.210624image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 1772
35.7%
2 1123
22.6%
0 1016
20.4%
3 660
 
13.3%
4 251
 
5.1%
5 96
 
1.9%
6 34
 
0.7%
7 13
 
0.3%
9 2
 
< 0.1%
8 2
 
< 0.1%
ValueCountFrequency (%)
0 1016
20.4%
1 1772
35.7%
2 1123
22.6%
3 660
 
13.3%
4 251
 
5.1%
5 96
 
1.9%
6 34
 
0.7%
7 13
 
0.3%
8 2
 
< 0.1%
9 2
 
< 0.1%
ValueCountFrequency (%)
9 2
 
< 0.1%
8 2
 
< 0.1%
7 13
 
0.3%
6 34
 
0.7%
5 96
 
1.9%
4 251
 
5.1%
3 660
 
13.3%
2 1123
22.6%
1 1772
35.7%
0 1016
20.4%

churn
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size43.7 KiB
False
4264 
True
705 
ValueCountFrequency (%)
False 4264
85.8%
True 705
 
14.2%
2023-03-08T12:46:55.413734image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Interactions

2023-03-08T12:46:37.850396image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:16.637674image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:22.924122image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:30.221997image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:37.500256image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:42.969779image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:48.052766image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:53.989631image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:59.358250image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:04.788073image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:09.834327image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:15.200518image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:20.954851image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:26.733131image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:32.399225image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:38.134111image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:17.070005image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:23.389198image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:30.686271image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:37.987274image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:43.253542image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:48.368378image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:54.319932image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:59.820349image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:05.197330image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:10.134694image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:15.501681image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:21.291548image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:27.079278image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:32.783818image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:38.429243image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:17.657970image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:23.858524image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:31.158799image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:38.356464image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:43.808540image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:48.782058image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:54.736976image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:00.161786image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:05.529837image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:10.681127image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:15.863397image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:21.712495image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:27.517650image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:33.115586image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:38.801715image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:18.135072image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:24.367323image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:31.679462image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:38.768219image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:44.115960image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:49.136069image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:55.036154image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:00.646509image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:05.816583image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:11.248348image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:16.180715image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:22.228857image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:27.993039image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:33.514960image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:39.115757image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:18.571720image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:24.857410image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:32.190132image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:39.223047image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:44.420923image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:49.469500image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:55.337363image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:00.985328image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:06.096448image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:11.740320image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:16.906178image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:22.715819image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:28.300697image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:34.093356image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:39.394557image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:18.868004image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:25.300118image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:32.662698image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:39.683699image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:44.807842image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:49.962602image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:55.652790image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:01.278020image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:06.359709image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:12.098517image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:17.265525image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:23.054817image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:28.582700image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:34.565219image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:39.773552image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:19.175508image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:25.776862image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:33.158667image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:39.985941image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:45.100937image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:50.355546image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:55.953394image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:01.639920image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:06.678802image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:12.409818image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:17.746339image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:23.379129image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:28.999597image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:34.985586image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:40.715738image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:19.476145image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:26.257350image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:33.650764image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:40.282031image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:45.398240image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:50.755397image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:56.269051image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:01.985026image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:07.147520image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:12.691794image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:18.229518image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:23.702088image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:29.416289image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:35.387505image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:41.095650image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:19.904218image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:26.705156image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:34.133129image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:40.620704image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:45.734481image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:51.054513image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:56.653698image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:02.270308image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:07.598278image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:12.976991image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:18.648409image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:24.015707image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:29.845404image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:35.716235image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:41.400156image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:20.210529image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:27.188553image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:34.619204image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:40.934610image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:46.040199image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:51.353045image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:57.002638image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:02.664667image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:07.900346image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:13.300636image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:18.987515image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:24.361979image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:30.229228image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:36.029844image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:41.879254image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:20.505529image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:27.667891image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:35.113667image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:41.227935image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:46.332204image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:51.715145image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:57.364814image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:03.077290image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:08.236268image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:13.618208image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:19.291443image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:24.808005image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:30.536242image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:36.347156image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:42.294656image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:20.836097image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:28.114184image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:35.568626image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:41.569888image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:46.696144image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:52.052951image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:57.684282image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:03.368586image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:08.653972image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:13.916367image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:19.645681image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:25.296391image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:30.826959image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:36.692054image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:42.716322image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:21.335378image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:28.606892image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:36.045047image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:41.989250image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:47.048041image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:52.402420image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:57.990780image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:03.746803image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:09.014813image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:14.249062image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:19.995504image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:25.717283image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:31.151491image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:36.992494image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:43.031986image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:21.893049image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:29.069831image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:36.540737image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:42.319058image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:47.404253image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:52.939714image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:58.315642image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:04.100510image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:09.283854image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:14.579615image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:20.329716image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:26.076544image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:31.501765image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:37.297156image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:43.385487image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:22.462717image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:29.555236image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:37.022219image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:42.665035image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:47.786641image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:53.525347image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:45:59.016244image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:04.413099image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:09.575630image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:14.902132image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:20.666924image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:26.399847image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:31.962448image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-03-08T12:46:37.577343image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Correlations

2023-03-08T12:46:55.681355image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
account_lengthvoice_messagesintl_minsintl_callsintl_chargeday_minsday_callsday_chargeeve_minseve_callseve_chargenight_minsnight_callsnight_chargecustomer_callsvoice_planintl_planchurn
account_length1.000-0.0090.0090.0180.0090.0050.0240.005-0.0100.007-0.0100.001-0.0060.001-0.0090.0000.0000.000
voice_messages-0.0091.0000.001-0.0110.0010.009-0.0040.0090.023-0.0010.023-0.0010.005-0.001-0.0120.9980.0000.110
intl_mins0.0090.0011.0000.0051.000-0.0220.009-0.0220.008-0.0100.008-0.0060.005-0.006-0.0140.0000.0000.056
intl_calls0.018-0.0110.0051.0000.005-0.0060.010-0.0060.0100.0070.010-0.013-0.001-0.013-0.0110.0000.0000.079
intl_charge0.0090.0011.0000.0051.000-0.0220.009-0.0220.008-0.0100.008-0.0060.005-0.006-0.0140.0000.0000.056
day_mins0.0050.009-0.022-0.006-0.0221.0000.0031.000-0.0120.006-0.0120.0030.0030.003-0.0010.0310.0380.363
day_calls0.024-0.0040.0090.0100.0090.0031.0000.0030.0010.0090.0010.002-0.0040.002-0.0130.0000.0000.026
day_charge0.0050.009-0.022-0.006-0.0221.0000.0031.000-0.0120.006-0.0120.0030.0030.003-0.0010.0320.0390.363
eve_mins-0.0100.0230.0080.0100.008-0.0120.001-0.0121.0000.0021.000-0.0160.017-0.016-0.0150.0390.0000.083
eve_calls0.007-0.001-0.0100.007-0.0100.0060.0090.0060.0021.0000.0020.008-0.0150.0090.0120.0000.0000.000
eve_charge-0.0100.0230.0080.0100.008-0.0120.001-0.0121.0000.0021.000-0.0160.017-0.016-0.0150.0400.0000.083
night_mins0.001-0.001-0.006-0.013-0.0060.0030.0020.003-0.0160.008-0.0161.0000.0171.000-0.0140.0110.0490.038
night_calls-0.0060.0050.005-0.0010.0050.003-0.0040.0030.017-0.0150.0170.0171.0000.017-0.0020.0000.0000.000
night_charge0.001-0.001-0.006-0.013-0.0060.0030.0020.003-0.0160.009-0.0161.0000.0171.000-0.0140.0100.0470.037
customer_calls-0.009-0.012-0.014-0.011-0.014-0.001-0.013-0.001-0.0150.012-0.015-0.014-0.002-0.0141.0000.0170.0210.313
voice_plan0.0000.9980.0000.0000.0000.0310.0000.0320.0390.0000.0400.0110.0000.0100.0171.0000.0000.110
intl_plan0.0000.0000.0000.0000.0000.0380.0000.0390.0000.0000.0000.0490.0000.0470.0210.0001.0000.259
churn0.0000.1100.0560.0790.0560.3630.0260.3630.0830.0000.0830.0380.0000.0370.3130.1100.2591.000

Missing values

2023-03-08T12:46:43.906216image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-03-08T12:46:44.743234image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

account_lengthvoice_planvoice_messagesintl_planintl_minsintl_callsintl_chargeday_minsday_callsday_chargeeve_minseve_callseve_chargenight_minsnight_callsnight_chargecustomer_callschurn
0128yes25no10.032.70265.111045.07197.49916.78244.79111.011no
1107yes26no13.733.70161.612327.47195.510316.62254.410311.451no
2137no0no12.253.29243.411441.38121.211010.30162.61047.320no
384no0yes6.671.78299.47150.9061.9885.26196.9898.862no
475no0yes10.132.73166.711328.34148.312212.61186.91218.413no
5118no0yes6.361.70223.49837.98220.610118.75203.91189.180no
6121yes24no7.572.03218.28837.09348.510829.62212.61189.573no
7147no0yes7.161.92157.07926.69103.1948.76211.8969.530no
8117no0no8.742.35184.59731.37351.68029.89215.8909.711no
9141yes37yes11.253.02258.68443.96222.011118.87326.49714.690no
account_lengthvoice_planvoice_messagesintl_planintl_minsintl_callsintl_chargeday_minsday_callsday_chargeeve_minseve_callseve_chargenight_minsnight_callsnight_chargecustomer_callschurn
4989150no0no8.322.24170.011528.90162.713813.83267.27712.020no
4990140no0no7.562.03244.711541.60258.610121.98231.311210.411yes
499197no0no8.852.38252.68942.94340.39128.93256.56711.541yes
499373no0no11.563.11177.98930.24131.28211.15186.2898.383no
499475no0no6.971.86170.710129.02193.112616.41129.11045.811no
499550yes40no9.952.67235.712740.07223.012618.96297.511613.392no
4996152no0no14.723.97184.29031.31256.87321.83213.61139.613yes
499761no0no13.643.67140.68923.90172.812814.69212.4979.561no
4998109no0no8.562.30188.86732.10171.79214.59224.48910.100no
499986yes34no9.3162.51129.410222.00267.110422.70154.81006.970no